Training in realistic situations often yields substantial performance improvement. With conventional technology, such realistic training can pose high risk to a participant, especially if the training involves performance of potentially dangerous tasks or operations in hostile and/or potentially threatening environments. So, to provide the participant with a reduced risk environment for training, the realistic situation can be simulated using motion capture. The term ‘motion capture’ as used herein generally refers to capturing any appropriate motion of an object in the real world using appropriate sensors and translating the motion in the real world to a motion in the virtual environment (which can also be characterized and interchangeably referred to as a virtual world).
In a motion capture simulation, typically a real world environment may be mapped to a virtual environment. Further, the real world environment may be different in proportion compared to the virtual environment. For example, the real world environment that is mapped to the virtual environment may be the size of a basketball court, while the corresponding virtual environment may be size of a large town. The difference in proportion may hinder a seamless movement in the virtual environment because the movement in the real world may be limited to the confines of the real world. For example, the movement of a participant in the real world may be limited within the boundaries of a room while the corresponding virtual environment is much larger than the room. The hindrance to the seamless movement in the virtual environment may affect a performance improvement of the participant. In view of the foregoing discussion of representative shortcomings, need for improved mapping from the real world to the virtual environment is apparent.